INTERLINKED POIs

SLIPO provides scalable workflows and tools for interlinking massive, heterogeneous, and incomplete POI data at a world-scale, thus facilitating the integration of fragmented, disconnected, ambiguous and multi-lingual POI datasets and addressing the lack of common POI identifiers.

ENRICHED AND FUSED POIs

SLIPO develops scalable workflows and tools for the fusion and semantic enrichment of Linked POI data. These tools address the problem of assembling partial, incomplete or even conflicting POI profiles, in order to derive more complete and consolidated profiles for each POI, enriched with additional spatial, temporal and thematic metadata.

QUALITY, ASSURANCE, PROVENANCE, EVOLUTION

SLIPO develops processes and metrics for quantifying and managing the quality improvements of Linked and fused POI datasets at each step of the value chain. In parallel, it provides processes for tracking information provenance and managing the evolution of Linked POI data.

VALUE ADDED ANALYTICS

SLIPO develops workflows and tools for performing advanced analytics and extracting added value from the integrated and enriched Linked POI data, leveraging the previous steps of the POI data lifecycle. This involves additional cycles of integration, through large scale aggregation and analytics in spatial, temporal and thematic dimensions.

The SLIPO Toolkit

SLIPO extends a series of tools, creating robust, efficient and scalable commercial-level software that focuses on the requirements and particularities of the POI integration and enrichment process.

Sparqlify and TripleGeo are powerful tools that handle the transformation of geospatial data from several sources and formats into RDF
triples.
LIMES is the state of the art tool for interlinking RDF data, taking also into account spatial dimensions of the entities.
FAGI is the first platform to allow fusion of geospatial Linked Data, supporting several thematic and spatial fusion actions.
DEER is a data enrichment framework that applies enrichment functions and
operators to discover implicit or explicit references of entities to external datasets.
OSMRec is a framework for the semantic enrichment and classification of geospatial entities.
SANSA is a distributed in memory framework for RDF that provides scalable inference and analytics capabilities for Linked Data.